Title
A Neural Approach to Source Dependence Based Context Model for Statistical Machine Translation.
Abstract
In statistical machine translation, translation prediction considers not only the aligned source word itself but also its source contextual information. Learning context representation is a promising method for improving translation results, particularly through neural networks. Most of the existing methods process context words sequentially and neglect source long-distance dependencies. In this p...
Year
DOI
Venue
2018
10.1109/TASLP.2017.2772846
IEEE/ACM Transactions on Audio, Speech, and Language Processing
Keywords
Field
DocType
Artificial neural networks,Context modeling,Decoding,Speech,Encoding,Semantics,Speech processing
Speech processing,Language translation,Programming language,Computer science,Machine translation,Phrase,Context model,Natural language processing,Artificial intelligence,Artificial neural network,Speech recognition,Semantics,Encoding (memory)
Journal
Volume
Issue
ISSN
26
2
2329-9290
Citations 
PageRank 
References 
5
0.45
50
Authors
8
Name
Order
Citations
PageRank
Kehai Chen14316.34
Tiejun Zhao2643102.68
Yang Muyun311229.50
Lemao Liu48718.74
Akihiro Tamura5114.58
Rui Wang6192.68
Masao Utiyama771486.69
Eiichiro SUMITA81466190.87